Research of Test Model for Eggshell Crack Detection

Jian Yang; Chun Yan Xia; He Pan; Ying Shi; Xiu Ying Li

doi:10.4028/www.scientific.net/AMR.846-847.655

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 846-847Research of Test Model for Eggshell Crack...

Research of Test Model for Eggshell Crack Detection

Abstract:

In order to realize the precise identification of eggshell crack, we design eggshell cracks detection method based on image processing and fuzzy neural network. Firstly this method gets two pieces image of eggs and processes, and then counts number of the same gray pixel. Determine five characteristic parameters as the input of fuzzy neural network. Set up a fuzzy neural network. Its structure is 5-10-1. Eggshell cracks and noise in egg images were distinguished using automatically learning and inference rules of fuzzy neural network. Use 147 groups of parameters for training network and rest 58 sample for verifying. Experimental result shows that the model can meet actual testing requirements with fast, stable, high precision and good robustness, easy to implement. Its precision reached 94.55%.

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Periodical:

Advanced Materials Research (Volumes 846-847)

Pages:

655-658

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.846-847.655

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Online since:

November 2013

Authors:

Jian Yang*, Chun Yan Xia, He Pan, Ying Shi, Xiu Ying Li

Keywords:

Computer Vision, Detection, Eggshell Cracks, Fuzzy Neural Network (FNN)

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